Paper
9 May 2000 Fundamental performance limits of power-spectrum condition-compliant watermarks
Jonathan K. Su, Bernd Girod
Author Affiliations +
Abstract
Our previous work introduced a stochastic framework for studying watermarking. When the receiver used direct correlation detection and the attack employed linear shift- invariant (LSI) filtering, the optimal attack consisted of Wiener filtering and adding noise. Resisting the Wiener attack led to a power-spectrum condition (PSC): the watermark and original power spectra should be directly proportional. PSC- compliant watermarks are most difficult to estimate from the watermarked document in the minimum mean-squared error sense. This paper investigates the fundamental limits of PSC- compliant watermarks; it has two main parts. First, expressions are derived for the detection-error probabilities after the Wiener attack with PSC-compliant Gaussian noise. An explicit relationship between attacked-document distortion and capacity results. The second part studies optimal LSI- filtering attacks and receivers. Because direct correlation detection is only optimal for white Gaussian noise (WGN), the Wiener attack and PSC may actually be suboptimal. It is shown that the PSC holds for a suboptimal, effective white-noise attack. The optimum attack is derived, but there does not appear to be an analytical solution for the optimum watermark power spectrum. Numerical experiments suggest that, as a rule of thumb, white watermarks perform well at lower distortions, while PSC-compliant watermarks perform better at higher distortions.
© (2000) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jonathan K. Su and Bernd Girod "Fundamental performance limits of power-spectrum condition-compliant watermarks", Proc. SPIE 3971, Security and Watermarking of Multimedia Contents II, (9 May 2000); https://doi.org/10.1117/12.384986
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Cited by 19 scholarly publications.
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KEYWORDS
Digital watermarking

Distortion

Receivers

Chromium

Sensors

Electronic filtering

Filtering (signal processing)

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